A method for reducing loss of large dynamic FFT operation by truncation and number system conversion

By optimizing the FFT operation process, selecting appropriate twitch factors and complex multiplication truncation bits, and converting the fixed-point FFT result into a floating-point representation, the signal distortion and resource waste caused by fixed-point FFT are solved, and the dynamic range and spectral accuracy are improved.

CN116244558BActive Publication Date: 2026-05-29THE 724TH RESEARCH INSTITUTE OF CHINA STATE SHIPBUILDING CORP LTD
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Patent Information

Application Number
CN202211443496.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-11-18
Publication Date
2026-05-29
Estimated Expiration
2042-11-18

AI Technical Summary

Technical Problem

In existing radar signal processing, fixed-point FFT operations result in excessive signal distortion and resource consumption, especially in low-gain wide-beam transmission mode, which limits the integrity of target information and the ability to process it with fine detail.

Method used

By selecting appropriate twitch factor quantization bits and complex multiplication truncation bits, and combining the number system conversion of the fixed-point FFT operation result to floating-point representation, the FFT operation process is optimized, dynamically improving the dynamic range of signal processing while preserving the spectral accuracy of small signals.

Benefits of technology

It effectively reduces FFT computation loss, improves dynamic range and spectral accuracy, reduces resource consumption and transmission bit width, and meets the needs of various engineering applications.

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Abstract

The application discloses a method for reducing the loss of large dynamic FFT operation by truncation and number system conversion, and relates to the field of radar signal processing. Firstly, by selecting appropriate rotation factor quantization bits and complex multiplication truncation bits, the full frequency domain precision loss is ensured to be not more than a fixed value under the condition of small signal input; then, whether to retain the bit width increased by complex addition operation is judged according to the order corresponding to the number of FFT points required to be operated; finally, according to the operation bit width truncation rule, after completing the entire FFT operation, the FFT operation result represented by fixed-point numbers is converted into the FFT operation result represented by floating-point numbers. The application can effectively retain the spectrum information under the condition of small signal input, avoid the signal distortion caused by the truncation in the FFT processing process, greatly improve the dynamic range, and provide good data support for subsequent fine processing.
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